幸运的因子
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资源简介
Lucky Factors
Campbell R. Harvey
Duke University, Durham, NC 27708 USA
National Bureau of Economic Research, Cambridge, MA 02138 USA
Yan Liu
Texas A&M University, College Station, TX 77843 USA
Current version: March 15, 2015
Abstract
We propose a new regression method to select amongst a large group of can-
didate factors | many of which might be the result of data mining | that
purport to explain the cross-section of expected returns. The method is robust
to general distributional characteristics of both factor and asset returns. We al-
low for the possibility of time-series as well as cross-sectional dependence. The
technique accommodates a wide range of test statistics such as t-ratios. While
our main application focuses on asset pricing, the method can be applied in any
situation where regression analysis is used in the presence of multiple testing.
This includes, for example, the evaluation of investment manager performance
as well as time-series prediction of asset returns.
Keywords: Factors, Variable selection, Bootstrap, Data mining, Orthogonal-
ization, Multiple testing, Predictive regressions, Fama-MacBeth, GRS.
